In this paper, we propose a visual interactive analysis approach for tropical cyclone trajectory prediction based on the support vector machine (SVM) regression method. We design a visual analysis interface that supports training data selection, model parameters adjustment and the visual assessment of model quality. This visual analysis approach can facilitate the prediction process and enable users to predict tropical cyclone trajectory easily. A case study with real data demonstrates the effectiveness of our approach.
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